Hi,
I’m currently working with panel data of counties in the US over 2 time periods - 2019 and 2014. I would like to estimate a regression of the difference in unemployment rates between 2019 and 2014 on a weighted average of the unemployment rate in counties in 2014. I have created my dependent variable (diff_unemp) using:
My explanatory variable (wtd_unemp) is formed by weighting the unemployment rate in 2014 with a measure of social connectedness. Since wtd_unemp only uses 2014 data, there is a missing value for it in every county in 2019.
My question is how do I actually run a regression of diff_unemp on wtd_unemp. diff_unemp has differenced observations in the t=2 period with missing values elsewhere while wtd_unemp has observations in the t =1 period with missing values in t=2 so I get an error saying "no observations" on trying to run
Here is an example of the first 3 counties with my panel ID indicating counties (geo_id), the time variable indicating whether time is 2014 (time = 1) or 2019 (time = 2), the unemployment rate, the differenced unemployment rate and the weighted unemployment rate.
Any help would be greatly appreciated!
I’m currently working with panel data of counties in the US over 2 time periods - 2019 and 2014. I would like to estimate a regression of the difference in unemployment rates between 2019 and 2014 on a weighted average of the unemployment rate in counties in 2014. I have created my dependent variable (diff_unemp) using:
Code:
gen diff_unemp = unemp_rate-L1.unemp_rate
My question is how do I actually run a regression of diff_unemp on wtd_unemp. diff_unemp has differenced observations in the t=2 period with missing values elsewhere while wtd_unemp has observations in the t =1 period with missing values in t=2 so I get an error saying "no observations" on trying to run
Code:
xtreg diff_unemp wtd_unemp
Code:
* Example generated by -dataex-. For more info, type help dataex clear input long geo_id float(time unemp_rate diff_unemp) double wtd_unemp 1001 1 8.531919 . 11.90644273715219 1001 2 3.676644 -4.855275 . 1003 1 8.596502 . 11.47575394038222 1003 2 4.255062 -4.34144 . 1005 1 14.186176 . 14.466721732840035 1005 2 9.166487 -5.01969 . end
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